An Interactive Scalable Knowledge Translation Tool for Network Meta-Analysis

Speaker(s)

Yu T
Université Paris Cité, Paris, France

Presentation Documents

OBJECTIVES: Network Meta-Analyses (NMAs) involve complex, voluminous information, challenging transparency, accessibility, and reproducibility. This makes data sharing difficult and hinders reviewers from easily accessing and understanding results, limiting broader application of the evidence. Existing tools often use traditional formats that fail to capture all information due to space constraints and do not meet diverse stakeholder needs. Our aim is to develop and release an interactive online scalable knowledge translation tool embedded in the NMAstudio application (http://www.nmastudioapp.com/), designed to summarize and present NMA findings transparently and comprehensively, addressing all end-user needs and assisting proper interpretation of the findings.

METHODS: We used a structured approach, starting with reviewing recent updates on reporting guidelines and existing tools to draft the initial version. An international expert committee of NMA specialists supports the development process. Stakeholders, including guideline developers, clinicians, policymakers, and meta-analysis professionals, will participate in two rounds of online interviews. The first round focuses on understanding stakeholder needs and improving the draft version of our tool. The second round involves user-testing to assess user experience.

RESULTS: Users can upload their data, run the analysis, and generate automatically tabular and graphical visualizations with key NMA details. Users can interact with all outputs through embedded functions and generate access tokens for project sharing and reproducibility. Using a network of 20 drugs for chronic plaque psoriasis as an example, we demonstrate how our tool facilitates the summary and communication of extensive NMA information and findings.

CONCLUSIONS: Our web application provides an interactive, flexible, and user-friendly solution for summarizing and presenting NMA findings, enhancing accessibility and usability for various stakeholders.

Code

MSR43

Topic

Study Approaches

Topic Subcategory

Literature Review & Synthesis, Meta-Analysis & Indirect Comparisons

Disease

No Additional Disease & Conditions/Specialized Treatment Areas